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Inter-module gap filling method for photon counting detectors based on dual acquisition.

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    Area of Science:

    • Medical Imaging
    • Photon Counting Detectors
    • Image Processing

    Background:

    • Photon counting detectors improve X-ray imaging resolution and signal-to-noise ratio.
    • Stitching detector modules causes localized information loss, hindering regional observation.

    Purpose of the Study:

    • To propose and validate the GFDA algorithm for filling inter-module gaps in photon counting detector images.
    • To enhance image restoration and detail retention in X-ray imaging.

    Main Methods:

    • Dual acquisition: main projection (short scan) and reference projection (vertical shift scan).
    • Alignment of region of interest.
    • Image stitching and fusion to recover missing information.

    Main Results:

    • The GFDA algorithm effectively recovers missing information, showing smoother and more perfect restoration.
    • Analysis of Siemens star and conch slice data confirmed improved information recovery.
    • The algorithm achieves better image restoration without additional scanning time.

    Conclusions:

    • The GFDA algorithm successfully addresses information loss from detector module stitching.
    • It offers improved image restoration and detail preservation in X-ray imaging.
    • The scalable GFDA algorithm is applicable to various photonic technology detectors.